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Adversarial Risk Analysis

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Release : 2015-06-30
Genre : Business & Economics
Kind : eBook
Book Rating : 401/5 ( reviews)

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Book Synopsis Adversarial Risk Analysis by : David L. Banks

Download or read book Adversarial Risk Analysis written by David L. Banks. This book was released on 2015-06-30. Available in PDF, EPUB and Kindle. Book excerpt: Winner of the 2017 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)A relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes. Adversarial Risk Analysis develops methods for allocating defensive or offensive resources against

Contribuciones Al Análisis de Riesgos Adversarios

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Release : 2018
Genre :
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Contribuciones Al Análisis de Riesgos Adversarios by : Jorge González Ortega

Download or read book Contribuciones Al Análisis de Riesgos Adversarios written by Jorge González Ortega. This book was released on 2018. Available in PDF, EPUB and Kindle. Book excerpt: Game theory and other group decision-making paradigms, see Gibbons [1992], have been regarded for a long time inadequate in most risk analysis applications. However, thanks to the urge to take into account the strategies of adversaries in contexts such as counter terrorism, economic competition or cybersecurity, a growing interest on these once dismissed methodologies has arisen. Adversarial Risk Analysis (ARA) [Ros Insua et al., 2009] is an emergent frameworkfor supporting a decision-maker (she) who faces opponents (he/they) in conflict situationsfor which the consequences are random and determined by all interacting agents' actions. ARA provides one-sided prescriptive help to the decision-maker, maximising her expected utility while treating her adversaries' decisions as random variables...

Security Risk Assessment

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Release : 2017-11-20
Genre : Science
Kind : eBook
Book Rating : 76X/5 ( reviews)

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Book Synopsis Security Risk Assessment by : Genserik Reniers

Download or read book Security Risk Assessment written by Genserik Reniers. This book was released on 2017-11-20. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the state-of-the-art of physical security knowledge and research in the chemical and process industries. Legislation differences between Europe and the USA are investigated, followed by an overview of the how, what and why of contemporary security risk assessment in this particular industrial sector. Innovative solutions such as attractiveness calculations and the use of game theory, advancing the present science of adversarial risk analysis, are discussed. The book further stands up for developing and employing dynamic security risk assessments, for instance based on Bayesian networks, and using OR methods to truly move security forward in the chemical and process industries.

Expert Judgement in Risk and Decision Analysis

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Release : 2021-02-19
Genre : Business & Economics
Kind : eBook
Book Rating : 741/5 ( reviews)

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Book Synopsis Expert Judgement in Risk and Decision Analysis by : Anca M. Hanea

Download or read book Expert Judgement in Risk and Decision Analysis written by Anca M. Hanea. This book was released on 2021-02-19. Available in PDF, EPUB and Kindle. Book excerpt: This book pulls together many perspectives on the theory, methods and practice of drawing judgments from panels of experts in assessing risks and making decisions in complex circumstances. The book is divided into four parts: Structured Expert Judgment (SEJ) current research fronts; the contributions of Roger Cooke and the Classical Model he developed; process, procedures and education; and applications. After an Introduction by the Editors, the first part presents chapters on expert elicitation of parameters of multinomial models; the advantages of using performance weighting by advancing the “random expert” hypothesis; expert elicitation for specific graphical models; modelling dependencies between experts’ assessments within a Bayesian framework; preventive maintenance optimization in a Bayesian framework; eliciting life time distributions to parametrize a Dirichlet process; and on an adversarial risk analysis approach for structured expert judgment studies. The second part includes Roger Cooke’s oration from 1995 on taking up his chair at Delft University of Technology; one of the editors reflections on the early decade of the Classical Model development and use; a current overview of the theory of the Classical Model, providing a deep and comprehensive perspective on its foundations and its application; and an interview with Roger Cooke. The third part starts with an interview with Professor Dame Anne Glover, who served as the Chief Scientific Advisor to the President of the European Commission. It then presents chapters on the characteristics of good elicitations by reviewing those advocated and applied; the design and development of a training course for SEJ; and on specific experiences with SEJ protocols with the intention of presenting the challenges and insights collected during these journeys. Finally, the fourth (and largest) part begins with some reflections from Willy Aspinall on his many experiences in applying the Classical Model in several application domains; it continues with related reflections on imperfect elicitations; and then it presents chapters with applications on medicines policy and management, supply chain cyber risk management, geo-political risks, terrorism and the risks facing businesses looking to internationalise.

Interpretable Machine Learning

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Release : 2020
Genre : Artificial intelligence
Kind : eBook
Book Rating : 528/5 ( reviews)

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Book Synopsis Interpretable Machine Learning by : Christoph Molnar

Download or read book Interpretable Machine Learning written by Christoph Molnar. This book was released on 2020. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

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